It is known that over half of previously surveyed surgeons performing Robot-Assisted Laparoscopic Surgery (RALS) and three-quarters of those performing Traditional Laparoscopic Surgery (TLS) experience intraoperative pain. This survey study aimed to expand upon the ongoing impact of that pain as well as perceived tool usability associated with TLS and RALS, for which considerably less documentation exists. A survey regarding the presence and impact, either immediate or ongoing, of intraoperative pain and Likert scale questions regarding tool usability was administered to TLS and RALS surgeons on the European Association for Endoscopic Surgery (EAES) mailing list. Prevalence statistics as well as trends based on biological sex and glove size were obtained from the 323 responses. Most respondents were right-handed European males (83-88%) with a medium glove size (55.8%). Moderate or severe shoulder symptoms were experienced by one-third of TLS surgeons. Twenty-one percent of RALS surgeons experienced neck symptoms that impacted their concentration. Small-handed surgeons experienced wrist symptoms significantly more frequently than large-handed surgeons, regardless of modality. RALS was associated with a significantly more optimal back and wrist posture compared to TLS. TLS surgeons reported increased ease with applying and moderating force while operating. These results suggest that intraoperative pain may be severe enough in many cases to interfere with surgeon concentration, negatively impacting patient care. Continuing to understand the relationship between tool usability and comfort is crucial in guaranteeing the health and well-being of both surgeons and patients.
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http://dx.doi.org/10.1007/s11701-023-01785-7 | DOI Listing |
Alzheimers Dement
December 2024
Boston University School of Public Health, Boston, MA, USA.
Background: Global health is increasingly burdened by oral diseases (ODs) affecting 3.9 billion people, and Alzheimer's disease with related dementias (AD/ADRD), impacting 46.8 million globally.
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December 2024
Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Background: Recent studies have demonstrated that deep learning of magnetic resonance imaging (MRI) brain scans can accurately predict Alzheimer's disease (AD) dementia and cognitive decline. However, the translational potential of this technique remains unfulfilled, as the underlying deep learning techniques are not yet available for immediate clinical use. To address this issue, we develop a web-based tool to facilitate real-time imaging data visualization and analyses, including brain image segmentation, cortical surface reconstruction, and early prediction of Alzheimer's disease dementia based on structural MRI data.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Background: Recent studies have demonstrated that deep learning of magnetic resonance imaging (MRI) brain scans can accurately predict Alzheimer's disease (AD) dementia and cognitive decline. However, the translational potential of this technique remains unfulfilled, as the underlying deep learning techniques are not yet available for immediate clinical use. To address this issue, we develop a web-based tool to facilitate real-time imaging data visualization and analyses, including brain image segmentation, cortical surface reconstruction, and early prediction of Alzheimer's disease dementia based on structural MRI data.
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December 2024
IPSIBAT (CONICET/National University of Mar del Plata), Mar del Plata, Buenos Aires, Argentina.
Background: In 2020, we developed LABPSI, a cognitive stimulation web lab. Usability analysis in MCI and healthy participants have already been studied, and currently, we performed it with acquired brain injuries (ABI) participants, as they can rehabilitate their cognitive symptoms and prevent the progression to dementia. Usability can be considered the ease of use of a certain product for a specific aim by a particular population.
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December 2024
MoCA Clinic and Institute, Greenfield Park, QC, Canada.
Background: XpressO from Montreal Cognitive Assessment (MoCA) is a self-administered, digital cognitive screening test composed of memory and executive function tasks. Its purpose is to provide a brief pre-screening of cognition in order to determine whether further cognitive testing is required. A previous validation study comparing the XpressO to the gold standard MoCA test revealed a strong predictive value.
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